Several publications and patent documents are cited throughout the specification in order to describe the state of the art to which this invention pertains. Each of these citations is incorporated by reference herein as though set forth in full. Color versions of certain figures and tables included herein have also been published in Y. R. Li et al, Nature Medicine Aug. 24, 2015, online publication doi: 10.1038 “backslash” nm.3933, and in the supplemental materials for that publication, and those figures and tables are incorporated by reference herein.
Autoimmune diseases affect up to 7-10% of individuals living in the Western Hemisphere1, representing a significant cause of chronic morbidity and disability. High rates of autoimmune disease comorbidity and familial clustering suggest that a strong genetic predisposition may underlie autoimmune disease susceptibility. Genome-wide association studies (GWAS) and immune-focused fine-mapping studies of autoimmune thyroiditis (AITD)2, psoriasis (PSOR)3, juvenile idiopathic arthritis (JIA)4, primary biliary cirrhosis (PBC)5, primary sclerosing cholangitis (PSC)6, rheumatoid arthritis (RA)7, celiac disease (CEL)8, inflammatory bowel disease (IBD, which includes Crohn's Disease (CD) and ulcerative colitis (UC)9), and multiple sclerosis (MS), have identified hundreds of autoimmune disease-associated single-nucleotide polymorphisms (SNPs) across the genome10. These studies and subsequent meta-analyses demonstrate that over half of all genome-wide significant (GWS) (PGWS<5×10−8) autoimmune disease associations are shared by at least two distinct autoimmune diseases11,12. However, when applied to heterogeneous diseases, classical meta-analysis approaches face limitations as they: 1) have limited power when disease-associated variants show variable effect sizes or even directions of effect across the traits, 2) may be affected by phenotypic heterogeneity and subject recruitment bias across studies, 3) often examine a candidate list or previously-discovered loci from single-disease studies, thereby missing the chance to identify novel associations, particularly those due to variants that are rarer or have smaller effect sizes, 4) do not fully adjust for population stratification and cryptic relatedness, and 5) may contain artifacts introduced by the use of multiple genotyping platforms or study sites.
While a few studies have merged case genotypes from multiple diseases in a limited way13-15, and a few loci have surfaced in independent GWAS studies across multiple autoimmune diseases, such as CLEC16A, first discovered in T1D16, and subsequently in MS17, RA18,19, CD20, PBC21, JIA19, and AA22, the degree to which genetic variants associated with one disease may be associated with the risk of other autoimmune diseases has not been systematically examined. Clearly, having this information would provide new therapeutic avenues for the treatment of such disorders.